{
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7-final"
  },
  "orig_nbformat": 2,
  "kernelspec": {
   "name": "python37764bitd2lconda94fc7ab78ae34cabbef0e75f5636f253",
   "display_name": "Python 3.7.7 64-bit ('d2l': conda)"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2,
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Help on package d2l:\n\nNAME\n    d2l - Saved source code for \"Dive into Deep Learing\" (https://d2l.ai).\n\nDESCRIPTION\n    Please import d2l by one of the following ways:\n    \n    from d2l import mxnet as d2l  # Use MXNet as the backend\n    from d2l import torch as d2l  # Use PyTorch as the backend\n    from d2l import tensorflow as d2l  # Use TensorFlow as the backend\n\nPACKAGE CONTENTS\n    mxnet\n    tensorflow\n    torch\n\nVERSION\n    0.14.3\n\nFILE\n    d:\\anaconda3\\envs\\d2l\\lib\\site-packages\\d2l\\__init__.py\n\n\n"
    }
   ],
   "source": [
    "import d2l\n",
    "help(d2l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "['__builtins__',\n '__cached__',\n '__doc__',\n '__file__',\n '__loader__',\n '__name__',\n '__package__',\n '__path__',\n '__spec__',\n '__version__',\n 'torch']"
     },
     "metadata": {},
     "execution_count": 7
    }
   ],
   "source": [
    "print(dir(d2l))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "['Accumulator', 'Animator', 'DATA_HUB', 'DATA_URL', 'Decoder', 'DotProductAttention', 'Encoder', 'EncoderDecoder', 'F', 'MLPAttention', 'MaskedSoftmaxCELoss', 'RNNModelScratch', 'Residual', 'Seq2SeqDecoder', 'Seq2SeqEncoder', 'SeqDataLoader', 'Timer', 'Vocab', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', 'abs', 'accuracy', 'annotate', 'arange', 'argmax', 'astype', 'build_array', 'collections', 'concat', 'corr2d', 'cos', 'cosh', 'count_corpus', 'd2l', 'data', 'defaultdict', 'display', 'download', 'download_all', 'download_extract', 'evaluate_accuracy', 'evaluate_accuracy_gpu', 'evaluate_loss', 'exp', 'float32', 'get_data_ch11', 'get_dataloader_workers', 'get_fashion_mnist_labels', 'grad_clipping', 'hashlib', 'int32', 'linreg', 'linspace', 'load_array', 'load_corpus_time_machine', 'load_data_fashion_mnist', 'load_data_nmt', 'load_data_time_machine', 'log', 'masked_softmax', 'math', 'matmul', 'meshgrid', 'mkdir_if_not_exist', 'nn', 'normal', 'np', 'numpy', 'ones', 'os', 'pd', 'plot', 'plt', 'predict_ch3', 'predict_ch8', 'predict_s2s_ch9', 'preprocess_nmt', 'random', 're', 'read_data_nmt', 'read_time_machine', 'reduce_sum', 'requests', 'reshape', 'seq_data_iter_consecutive', 'seq_data_iter_random', 'sequence_mask', 'set_axes', 'set_figsize', 'sgd', 'show_images', 'show_trace_2d', 'shutil', 'sin', 'sinh', 'size', 'squared_loss', 'stack', 'synthetic_data', 'sys', 'tanh', 'tarfile', 'tensor', 'time', 'to', 'tokenize', 'tokenize_nmt', 'torch', 'torchvision', 'train_2d', 'train_ch11', 'train_ch3', 'train_ch6', 'train_ch8', 'train_concise_ch11', 'train_epoch_ch3', 'train_epoch_ch8', 'train_s2s_ch9', 'transforms', 'transpose', 'truncate_pad', 'try_all_gpus', 'try_gpu', 'use_svg_display', 'zeros', 'zipfile']\n"
    }
   ],
   "source": [
    "from d2l import torch as d2l\n",
    "print(dir(d2l))"
   ]
  }
 ]
}